Spurred by increasingly unpredictable weather, high penetration of renewable resources and a period of focused US government policy, it is widely expected that microgrids within the electric distribution system will show exponential growth in the coming decade. Microgrids comprise of power generation, delivery and consumption assets within restricted electrical boundaries and under contiguous control oversight that enables holistic management of these assets. Microgrids can be islanded and operated independent of a larger electric power network, and as such, a primary function of microgrids is to enhance the energy reliability of the underlying loads. In this work, we focus on naval shipboard power systems. Apart from being islanded, in the true sense, resiliency and damage mitigation are key considerations in the design and operation of these power systems.Islanded power systems encompass a rich diversity of discrete and continuous dynamic behavior in multiple time-scales. A high penetration of devices with power electronics interface, low inherent system inertia, and high density of switching devices can lead to rapid disturbance propagation and system failure without advanced damage mitigation strategies.

Hybrid systems formalism incorporates continuous dynamics as well as discrete switching behavior into a modeling and control framework, thus allowing a complete system description while crystallizing concepts of safety into system design criteria. We build on existing work to enhance a Dynamic Mixed Integer Programming (DMIP) model of a power system that combines continuous time differential algebraic models with switching dynamics synthesized into mixed integer inequalities. We use this model to derive an optimal system reconfiguration strategy to prevent voltage collapse of a benchmark shipboard power system. However, this methodology is restricted by the computational complexity of dynamic programming and scalability of non-automated processes.

To overcome some of these limitations, we derive a hybrid automaton model of a power system as a Discrete Event System (DES) plant and controller. The DES plant consists of a switched continuous system with an interface. The system state space is categorized based on safety criteria and discrete control specifications are embedded as transition rules within the DES controller. The DES controller searches for feasible control policies that drive the system trajectories from unsafe states to safe states. We define metrics to quantify the performance of these policies, thus allowing the derivation of the most suitable policy for a set of design specifications and disturbance type. Applications in voltage control, frequency control and dynamic service restoration is presented on a benchmark power system with approximately forty continuous states and eighteen thousand discrete states.

To enable the analysis, we build a computational framework based on efficient symbolic computation tools in Mathematica and numerical integration tools in Matlab / Simulink so that the methodology can be replicated for a wide variety of applications. The framework is quite general, and may be expanded to problems beyond power systems.